Optimizing Employee Well-being and Retention during Electronic Health Record Modernization

背景：VA正在进行的电子健康记录现代化（EHRM）是美国最大的 复杂的组织活动。VA领导层认识到， 提供高质量的护理取决于人员配备齐全和高效的工作队伍。当前EHRM 这一倡议如果执行不力，将对这一业务需求构成重大威胁。早期的工作表明， 第一个经历转变的位点（即，上线）对临床医生具有深刻的破坏性， 对EHR的看法，员工士气和提供临床护理的能力。退伍军人事务部的领导人 迫切需要的信息，以改变EHRM的过程，以确保一个充分的工作人员和高福利 健康的劳动力。 意义：拟议的研究将产生及时的数据驱动的见解， 领导者制定快速决策和战略，以减轻不良的劳动力结果 EHRM导致的员工流失、缺勤、职业倦怠。调查结果还将为战略交付提供信息 工作场所的干预，确定VA临床医生亚组在最高风险的不利劳动力的结果。 EHRM预计将持续数年，研究结果将提供可操作的见解，以支持 在等待启用的设施中做好变革准备，并改进企业人力资源管理流程。 创新和影响：研究的关键创新是产生新的科学知识， 全面识别EHRM如何影响四个劳动力的结果：营业额，缺勤，倦怠， 订婚从这项研究中获得的新见解将提供及时的见解，以有意义地改善 在VA的EHRM课程，并指导其他非VA卫生系统规划自己的EHRM。 具体目标：项目具体目标包括：1）研究EHRM实施与 劳动力成果使用计量经济学方法，2）探索关键EHRM相关主题与 劳动力成果使用纵向定性方法和3）设计和管理一项调查，以确定 与劳动力成果相关的关键EHRM因素。 方法：这项多方法研究将探讨全国各地的VA EHRM的影响。数据源 将包括来自VA公司数据仓库、人事和会计的员工信息 集成数据文件、HR SMART数据库、VA所有员工调查和半结构化面试。在 目的1，将采用准实验研究设计来定量识别总体和亚组效应 的EHRM利用伪随机变化交错实施EHRM。在目标2中，我们将 收集和分析关键信息提供者访谈的定性数据，以探索EHRM相关要素 与劳动力成果相关。将从研究中心的剩余和独立临床医生处收集数据 预计将在接下来的几个月内上线。目标3将应用多变量回归技术， 使用新的调查数据，了解EHRM要素与劳动力成果之间的关系 在这项研究中收集。 实施/后续步骤：研究结果将用于为工具的设计和修改提供信息， 有效实施新的EHR和/或促进积极的劳动力成果。这包括一个新的战略 将与VA小组合作编写自下而上改进EHRM的方法手册 持份者产品开发将利用与运营合作伙伴的强大工作关系 包括职能倡导者办公室的领导人在内的先前研究中开发的。

Background: VA’s ongoing electronic health record modernization (EHRM) represents one of the largest and complex organizational initiatives VA has undertaken. VA leadership recognizes the ability to consistently provide high quality care depends on a fully staffed and highly effective workforce. VA’s current EHRM initiative, if poorly implemented, is a major threat to this operational need. Early work indicates that EHRM at the first site to undergo transition (i.e., go-live) was profoundly disruptive to clinicians, adversely impacting perceptions of the EHR, employee morale and the ability to deliver clinical care. VA operational leaders are in urgent need of information to alter the course of EHRM to ensure the well-being of a fully staffed and high functioning health workforce. Significance: The proposed study will generate timely data-driven insights to enable operational and facility leaders to enact fast-paced decisions and strategies designed to mitigate undesirable workforce outcomes resulting from EHRM including turnover, absenteeism, burnout. Findings will also inform the strategic delivery of workplace intervention by identifying VA clinician subgroups at highest risk of adverse workforce outcomes. EHRM is expected to continue for several years, and study findings will provide actionable insights to support change readiness and improve EHRM processes at facilities awaiting go-live. Innovation and Impact: The key innovation of the study is the generation of new scientific knowledge that comprehensively identifies how EHRM affects four workforce outcomes: turnover, absenteeism, burnout, and engagement. New insights gained from this study will provide timely insights to meaningfully improve the course of EHRM in VA and guide other non-VA health systems planning their own EHRM. Specific Aims: Project specific aims include: 1) examine the association between EHRM implementation and workforce outcomes using econometric methods, 2) explore key EHRM related themes associated with workforce outcomes using longitudinal qualitative methods and 3) design and administer a survey to identify key EHRM factors associated with workforce outcomes. Methodology: This multi-methods study will examine the effects of EHRM across VA nationally. Data sources will include employee information from the VA Corporate Data Warehouse, Personnel and Accounting Integrated Data files, HR SMART database, the VA All Employee Survey, and semi-structured interviews. In Aim 1, a quasi-experimental study design will be applied to quantitatively identify overall and subgroup effects of EHRM by leveraging pseudo-random variation in the staggered implementation of EHRM. In Aim 2, we will collect and analyze qualitative data from key informant interviews to explore EHRM-related elements associated with workforce outcomes. Data will be collected from remaining and separated clinicians at sites expected to go-live in the proceeding months. Aim 3 will apply multivariable regression techniques to examine relationships between perceptions of EHRM elements and workforce outcomes using new survey data collected in this study. Implementation/Next Steps: Study findings will be used to inform the design and modification of tools to effectively implement the new EHR and/or promote positive workforce outcomes. This includes a new strategic playbook of bottom-up approaches to improve EHRM, to be developed in collaboration with a panel of VA stakeholders. Product development will capitalize on strong working relationships with operational partners developed in prior research including leaders of the Office of the Functional Champion.